Determinants of Intention to Use ChatGPT for Educational Purposes: Findings from PLS-SEM and fsQCA

By Behzad Foroughi, Madugoda Gunaratnege Senali, Mohammad Iranmanesh, Ahmad A. Khanfar, Morteza Ghobakhloo, Nagaletchimee Annamalai, Bita Naghmeh-Abbaspour. International journal of human computer interactions, 2023

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Abstract ChatGPT can revolutionize education by enhancing student engagement and making learning more personalized. Drawing on UTAUT2, this study investigated determinants of intention to use ChatGPT for educational purposes. Data were gathered from 406 Malaysian students and analyzed using a hybrid approach including “partial least squares” (PLS) and “fuzzy-set qualitative comparative analysis” (fsQCA). PLS showed that performance expectancy, effort expectancy, hedonic motivation, and learning value significantly influence the intention to use ChatGPT. Furthermore, we found that personal innovativeness and information accuracy negatively moderate the associations between ChatGPT use and its determinants. While PLS demonstrated that social influence, facilitating conditions, and habit do not affect ChatGPT use, fsQCA revealed that all factors might affect the intention to use ChatGPT. fsQCA suggested that eight combinations of factors may lead to high ChatGPT use. The results hold various implications for ChatGPT developers, instructors, and universities and provide insights for accelerating ChatGPT adoption.

Subfields: Health Informatics, Information Systems and Management, Management Information Systems

View Paper: https://www.semanticscholar.org/paper/5bf6dd9238df30ffe498cab59dad67ae4b26f3ea

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